Abstract
In this paper we face the problem of determining the best partial order among the subgoals of a query in order for this query to be evaluated under Independent AND Parallelism. This is the most common source of parallelism exploited by the different models that have been proposed to evaluate logic programs in parallel. This problem is proved to be NP-hard, so every model utilises its own heuristic strategy in order to estimate the best ordering. Here, a Genetic approach is proposed and compared to conventional heuristic ones. The experimental results show that the Genetic Algorithm produces better solutions, as well as comparable execution times for reasonably sized problems.
This work has been partially supported by the University of Oviedo under the project DF-96-513-10.
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Vela, C.R., Alonso, C., Varela, R., Puente, J. (1997). A genetic approach to computing Independent And Parallelism in logic programs. In: Mira, J., Moreno-Díaz, R., Cabestany, J. (eds) Biological and Artificial Computation: From Neuroscience to Technology. IWANN 1997. Lecture Notes in Computer Science, vol 1240. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0032516
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DOI: https://doi.org/10.1007/BFb0032516
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